Triple
T21042348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makepung |
E518356
|
entity |
| Predicate | animalDecoration |
P3351
|
FINISHED |
| Object | colorful ornaments |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: colorful ornaments | Statement: [Makepung, animalDecoration, colorful ornaments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: animalDecoration Context triple: [Makepung, animalDecoration, colorful ornaments]
-
A.
decorations
Indicates that one entity adds, provides, or serves as ornamental or decorative elements for another entity.
-
B.
decoration
chosen
Indicates that one entity serves as an ornament or embellishing element for another entity, enhancing its appearance or style.
-
C.
decorativeCategory
Indicates that one entity is classified as belonging to a particular decorative style, theme, or ornamentation category of another entity.
-
D.
decorationShape
Indicates the geometric or visual form that a decorative element or ornament takes in relation to the object it adorns.
-
E.
toyTreatment
Indicates a relationship where one entity applies a treatment, procedure, or intervention to a toy or toy-like object.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcf0b27881909d1c5b58be387a74 |
completed | April 21, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf6728881908a2a43a5c8804a2a |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:15 p.m.